MATH 569 -- Survey of Statistics

## MATH 569 Survey of Statistics Fall 2009

 INSTRUCTOR:     Prof. KARIN REINHOLD     Office: ES 123A     Phone: 442-4641     e-mail: reinhold@albany.edu     Office Hours: 8:30-9:30.     Class Room: ES 143. We may use AS 0013 later on. TEXT: non--assigned. Here are some books I will be using.     1. Statistics, by Freedman, Pisani, Purves -- Norton        This book is for begining statistics but it has excellent conceptual explanations, very readable.     2. Intro Stats, by De Veaux, Velleman & Bock -- Pearson, Prentice Hall.        This book is for begining statistics but it is very amenable and has very good explanations.     3. Probability and Statistics for engineering and the sciences, by Devore -- Thomson\Brooks+Cole.        This one is more mathematical rigourous but it is dry and the problems are not so engaging.    4. UCLA Probabilty and Statistics EBook another online book    5. Introductory Statistics with R, by Dalgaard -- Srpinger.        This book is a consise intro to R.    6. Simple R, by Verzani, click here for on-line book.    7. Statistics and Data with R, by Cohen & Cohen -- Wiley.       This one has good problems to do statistics in R

### Course description:

In this course we will cover basic statistical principles, startinf from data description and data gathering, moving to statistical estimation theory and statistical desicion theory. Among the test we will study simple test of hypothesis for one and two populations. Chi--square test, ANOVA and non parametric tests. We will also study simple and multiple regression.

The goals of this course is to adquire sufficinet knowledge to carry out simple statistical studies with focus on the following steps:

Determine what question you would like to answer. Designe how to obtain data to help answer the question. Display and analyze the data. Draw inferences from your data. Evaluate your study and or model.

Your grade wil be based on projects (40%), midterm exam (30%) and a final exam (30%). The projects will include a semester long portfolio where you will keep a log of the projects, and the minute quizzes. To pass the course you need to obtain a total average of 50\% or more, must not obtain a grade of 30 or less in more than one exam or in the combination of all quizzes.

It is your responsibility to be aware of the dates of the exams and the content and due date of assignments. If you miss a class, it is your responsibility to be aware of the topics discussed during that class, the assigned homework and the possibly given assignment. There are no make ups for in-class quizzes missed.

There is no reason to miss an exam other than getting sick (bring note from doctor), being on a team that has a game at the same time an exam is given (bring a note from your coach), or a death or serious illness in your family (bring a note from your family). In the event you can not attend an exam, you must notify me in advance, otherwise your grade for that exam will be 0. You can contact me by phone (leave a message if I'm not in), stop by my office (leave a note if I'm not in) or send me an e-mail.

EXAM SCHEDULE:
Midterm Exam: Oct. 17.
Final Exam: Dec 5

Class 1: Sept 5. Displaying data, box plots and histograms. Gathering data. Measures of center and spread.
Class 2: Sept 12. Probabilities: basic properties. Independence. Conditional probability. Probability models: Binomial, Poisson, normal.
Class 3: Sept 26. Expected value and variance.
Class 4: Oct 3. Sampling distributions. Estimation, confidence intervals.
Class 5: Oct 10. Tests of hypothesis: conditions, p--values, type I and II errors.
Class 6: Oct 17 - Midterm - Comparing two populations.
Class 7: Oct 24. Chi square tests.
Class 8: Oct 31. ANOVA.
Class 9: Nov 7. Simple Regression
Class 10: Nov 14. Multiple regression.
Class 11: Nov 21. Non parametric tests.
Class 12: Dec 5. -Final- presentations.

### Data Files:

computational stats: Susan Holms
www-stat.stanford.edu/~susan/courses/s227/#x1-100001.6